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1.
Chinese Journal of Applied Clinical Pediatrics ; (24): 1879-1882, 2022.
Article in Chinese | WPRIM | ID: wpr-989973

ABSTRACT

Objective:To evaluate the activity of iduronate-2-sulfatase (IDS) in fetal villi and peripheral blood plasma of pregnant women at high risk of mucopolysaccharidosis type Ⅱ (MPS Ⅱ), and to discuss the application of gene analysis in prenatal diagnosis of MPS Ⅱ.Methods:The enzymatic testing and gene analysis results of 23 pregnant women at high risk of MPS Ⅱ, who underwent prenatal diagnosis in Guangzhou Women and Children′s Medical Center from February 2013 to December 2020, were analyzed retrospectively.The IDS activity in fetal villi (30 cases) and plasma (28 cases) was detected by artificial substrate fluorescence.The IDS activity in fetal villi (28 cases) and plasma (34 cases) of normal pregnant women was taken as control.Meanwhile, the fetal villi of both pregnant women at high risk of MPS Ⅱ and normal pregnant women were also analyzed by gene testing and for fetal sex identification.Data were compared between groups by the independent samples t test. Results:The normal reference values of the IDS activity in fetal villi and plasma of normal pregnant women were(71.2±23.4) nmol/(mg·4 h) and (611.1±114.5) nmol/(mL·4 h), respectively.Among the 30 cases of high-risk fetal villi, the IDS activity in fetal villi of 8 affected male fetuses was (1.7±0.3) nmol/(mg·4 h), which was significantly lower than that of 11 unaffected male fetuses (83.2±6.3) nmol/(mg·4 h) and that of 9 non-carrier female fetuses (80.0±7.5) nmol/(mg·4 h) ( t=10.8, 8.8; all P<0.01). Meanwhile, the IDS activity was measured in the maternal peripheral plasma of 28 pregnant women at high risk of MPS Ⅱ.Among them, the IDS activity in 8 affected male fetuses was(225.4±20.5) nmol/(mL·4 h), which was significantly lower than that in non-affected male fetuses[(451.0±15.1) nmol/(mL·4 h)] and that in non-carrier female fetuses[(467.7±45.3)nmol/(mL·4 h)]. Eight known pathogenic mutations were found in 30 cases at high risk of MPS Ⅱ of fetal villi, and the mutation types were c. 1048A>C, c.212G>A, c.514C>T, c.257C>T, c.425C>T, and c. 998C>T.Of the 8 cases, 6 affected male fetuses had significantly reduced IDS activities, and the other 2 female carriers had normal IDS enzyme activities. Conclusions:The IDS activity in fetal villi and peripheral plasma of pregnant woman is consistent with the gene analysis results.The IDS activity has an important reference value for the prenatal diagnosis of MPS Ⅱ in the first trimester.When no genetic mutations are found in the probands or the pathogenicity of the new mutation remains unclear, the IDS activity in fetal villi can be detected separately for the prenatal diagnosis of MPS Ⅱ.

2.
Chinese Journal of Medical Imaging Technology ; (12): 1799-1803, 2019.
Article in Chinese | WPRIM | ID: wpr-861135

ABSTRACT

Objective: To explore the clinical applicability of a deep learning based bone age assessment system of children and adolescents in Guizhou. Methods: The left hand-wrist radiographs of 148 children and adolescents aged from 2 years to 17 years were assessed independently by three experts who were trained with the CH 05 RUS-CHN method, their mean estimates results were used as the reference standard. The estimates of the deep learning model (model group) and two residents (control group) were evaluated compared with the reference standard, respectively. mean absolute error (MAE) of bone age estimates and the percentage of samples with absolute error (AE) ≤1.0 year were calculated. Results: MAE of the model group was 0.295 [95%CI (0.238, 0.352)] years, with absolute error ≤1 years of 93.92% (139/148). Doctor A of the control group recorded MAE was 0.438 [95%CI (0.369, 0.508)] years, with 89.19% absolute error ≤1.0 years of 89.19% (132/148); doctor B recorded MAE of 0.360 [95%CI (0.295, 0.425)] years, with absolute error ≤1.0 years of 89.86% (133/148). The MAE of model group was significantly lower than that of doctor A (t=-3.071, P=0.002), but not for the doctor B (t=-1.563, P=0.120). Conclusion: When bone age assessed with the CH 05 RUS-CHN method for Guizhou children and adolescents, the deep learning model can estimate bone age with accuracy similar to or even better than that of control group radiologists.

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